On-line estimation of the final prediction error via recursive least-squares method

This paper starting from the very first principle presents a derivation of an equation estimating of the final prediction error for a neural network under the recursive least square framework. The equation is in the form: hhPEiF iT 1⁄4 hTEiT N þ d1 N d2 , where d1 and d2 are some values determined by the gradient of the nonlinear mapping at the true system parameter. A cheap way of estimating such prediction error based on the information obtained via the recursive least square training method is suggested. r 2006 Elsevier B.V. All rights reserved.